The unique properties of superconductivity can be exploited to provide the ultimate in electronic technology for systems such as ultra-precise analogue-to-digital and digital-to-analogue converters, precise DC and AC voltage standards, ultra high speed logic circuits and systems (both digital and hybrid analogue-digital systems), and very high throughput network routers and supercomputers which would have superior electrical performance at lower overall electrical power consumption compared to systems with comparable performance which are fabricated using conventional room temperature technologies. This potential for high performance electronics with reduced power consumption would have a positive impact on slowing the increase in the demand for electrical utility power by the information technology community on the overall electrical power grid. However, before this technology can be successfully brought to the commercial market place, there must be an aggressive investment of resources and funding to develop the required infrastructure needed to yield these high performance superconductor systems, which will be reliable and available at low cost. The author proposes that it will require a concerted effort by the superconductor and cryogenic communities to bring this technology to the commercial market place or make it available for widespread use in scientific instrumentation.

A technique for suppressing the clipping noise of an analogue-to-digital converter (ADC) is proposed to realize a cognitive radio transceiver that offers high sensitivity carrier-sensing. When a large bandwidth cognitive radio transceiver performs carrier-sensing, it must receive a radio wave that includes many primary user transmissions. The radio wave may have high peak-to-average power ratio (PAPR) and clipping noise may be generated. Clipping noise becomes an obstacle to the achievement of high-sensitivity carrier-sensing. In the proposed technique, the original values of the samples clipped by an ADC are estimated by interpolation. Polynomial spline interpolation to the clipped signal is performed in the first step, and then SINC function interpolation is applied to the spline interpolated signal. The performance was evaluated using the signals with various PAPR. It has been found that suppression performance has a dependency on the number of samples clipped at once rather than on PAPR. Although there is an upper limit for the number of samples clipped at once that can be compensated with high accuracy, about 20 dB suppression of clipping noise was achieved with the medium degree of clipping.